Ambient affiliation: A linguistic perspective on Twitter

By Michele Zappavigna. New Media & Society, 2011

552 citations recorded by the source corpus.

Subfields: Language and Linguistics, Literature and Literary Theory, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/d735762d97a991addee489c9a667881562aa87be

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Language and Linguistics

1. Mohamed M. Mostafa
2. Marloes Geboers
3. Chad Thomas Van De Wiele
4. Deen Freelon

In Literature and Literary Theory

1. Mohamed M. Mostafa
2. Marloes Geboers
3. Chad Thomas Van De Wiele
4. Deen Freelon

In Human-Computer Interaction

1. Mohamed M. Mostafa
2. Marloes Geboers
3. Chad Thomas Van De Wiele
4. Deen Freelon

Citations in the corpus

• On the Interpretation of Digital Trace Data in Communication and Social Computing Research (2014, background): “Of the nine studies that offer one or more interpretation, four present them as unsupported statements (Anstead & O’Loughlin, 2011; Elmer, 2013; Moe, 2012; Zappavigna, 2011).”
• More than words: Social networks' text mining for consumer brand sentiments (2013, methodology): “Zappavigna (2011) used a large corpus of tweets (45,000) posted immediately after Obama’s US presidential elections victory in 2008.”
• Machine Vision and Social Media Images: Why Hashtags Matter (2020, background): “In the context of social media, this is no different; almost “more than words,” hashtags are linguistic markers that function as online meta-data (Zappavigna, 2011).”